"""
数据适配器

提供各种数据源的统一访问接口。
"""

from typing import Dict, List, Any, Optional, Union
from datetime import datetime, timedelta
from abc import ABC, abstractmethod
import asyncio
import pandas as pd


class DataAdapter(ABC):
    """
    数据适配器基类
    
    定义所有数据适配器的通用接口。
    """
    
    def __init__(self, name: str):
        """
        初始化数据适配器
        
        Args:
            name: 适配器名称
        """
        self.name = name
        self._initialized = False
        self._connection = None
    
    @abstractmethod
    async def initialize(self) -> None:
        """初始化适配器连接"""
        pass
    
    @abstractmethod
    async def get_market_data(
        self,
        symbols: List[str],
        start_date: datetime,
        end_date: datetime,
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取市场数据
        
        Args:
            symbols: 股票代码列表
            start_date: 开始日期
            end_date: 结束日期
            fields: 数据字段列表
            
        Returns:
            市场数据字典
        """
        pass
    
    @abstractmethod
    async def get_fundamental_data(
        self,
        symbols: List[str],
        metrics: List[str],
        period: str
    ) -> Dict[str, Any]:
        """
        获取基本面数据
        
        Args:
            symbols: 股票代码列表
            metrics: 财务指标列表
            period: 报告期间
            
        Returns:
            基本面数据字典
        """
        pass
    
    async def get_alternative_data(
        self,
        data_type: str,
        parameters: Dict[str, Any]
    ) -> Dict[str, Any]:
        """
        获取另类数据（可选实现）
        
        Args:
            data_type: 数据类型
            parameters: 查询参数
            
        Returns:
            另类数据字典
        """
        raise NotImplementedError(f"Alternative data not supported by {self.name}")
    
    async def get_real_time_data(
        self,
        symbols: List[str],
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取实时数据（可选实现）
        
        Args:
            symbols: 股票代码列表
            fields: 数据字段列表
            
        Returns:
            实时数据字典
        """
        raise NotImplementedError(f"Real-time data not supported by {self.name}")
    
    async def store_data(
        self,
        data: Dict[str, Any],
        data_type: str,
        metadata: Optional[Dict[str, Any]] = None
    ) -> bool:
        """
        存储数据（可选实现）
        
        Args:
            data: 要存储的数据
            data_type: 数据类型
            metadata: 元数据
            
        Returns:
            存储是否成功
        """
        raise NotImplementedError(f"Data storage not supported by {self.name}")
    
    async def get_status(self) -> Dict[str, Any]:
        """
        获取适配器状态
        
        Returns:
            状态信息字典
        """
        return {
            "name": self.name,
            "initialized": self._initialized,
            "connection_status": "connected" if self._connection else "disconnected"
        }
    
    async def cleanup(self) -> None:
        """清理资源"""
        if self._connection:
            try:
                await self._connection.close()
            except Exception:
                pass
        self._initialized = False


class TushareAdapter(DataAdapter):
    """
    Tushare数据适配器
    
    提供Tushare数据源的访问接口。
    """
    
    def __init__(self, token: str):
        """
        初始化Tushare适配器
        
        Args:
            token: Tushare API token
        """
        super().__init__("tushare")
        self.token = token
        self._api = None
    
    async def initialize(self) -> None:
        """初始化Tushare连接"""
        try:
            import tushare as ts
            ts.set_token(self.token)
            self._api = ts.pro_api()
            self._initialized = True
            self._connection = self._api
        except ImportError:
            raise ImportError("tushare package not installed")
        except Exception as e:
            raise ConnectionError(f"Failed to initialize Tushare: {e}")
    
    async def get_market_data(
        self,
        symbols: List[str],
        start_date: datetime,
        end_date: datetime,
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取市场数据
        
        Args:
            symbols: 股票代码列表
            start_date: 开始日期
            end_date: 结束日期
            fields: 数据字段列表
            
        Returns:
            市场数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        # 字段映射
        field_mapping = {
            "open": "open",
            "high": "high", 
            "low": "low",
            "close": "close",
            "volume": "vol",
            "amount": "amount"
        }
        
        tushare_fields = [field_mapping.get(f, f) for f in fields]
        
        data = {}
        for symbol in symbols:
            try:
                # 转换股票代码格式
                ts_code = self._convert_symbol(symbol)
                
                # 获取日线数据
                df = self._api.daily(
                    ts_code=ts_code,
                    start_date=start_date.strftime("%Y%m%d"),
                    end_date=end_date.strftime("%Y%m%d"),
                    fields=f"ts_code,trade_date,{','.join(tushare_fields)}"
                )
                
                if not df.empty:
                    df['trade_date'] = pd.to_datetime(df['trade_date'])
                    df = df.sort_values('trade_date')
                    data[symbol] = df.to_dict('records')
                else:
                    data[symbol] = []
                    
            except Exception as e:
                data[symbol] = {"error": str(e)}
        
        return {
            "data": data,
            "source": "tushare",
            "timestamp": datetime.now(),
            "fields": fields
        }
    
    async def get_fundamental_data(
        self,
        symbols: List[str],
        metrics: List[str],
        period: str
    ) -> Dict[str, Any]:
        """
        获取基本面数据
        
        Args:
            symbols: 股票代码列表
            metrics: 财务指标列表
            period: 报告期间
            
        Returns:
            基本面数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        data = {}
        for symbol in symbols:
            try:
                ts_code = self._convert_symbol(symbol)
                
                # 获取财务数据
                if period == "quarterly":
                    # 获取季报数据
                    income_df = self._api.income(ts_code=ts_code, period="Q")
                    balance_df = self._api.balancesheet(ts_code=ts_code, period="Q")
                    cashflow_df = self._api.cashflow(ts_code=ts_code, period="Q")
                else:
                    # 获取年报数据
                    income_df = self._api.income(ts_code=ts_code, period="A")
                    balance_df = self._api.balancesheet(ts_code=ts_code, period="A")
                    cashflow_df = self._api.cashflow(ts_code=ts_code, period="A")
                
                # 合并财务数据
                fundamental_data = {
                    "income": income_df.to_dict('records') if not income_df.empty else [],
                    "balance": balance_df.to_dict('records') if not balance_df.empty else [],
                    "cashflow": cashflow_df.to_dict('records') if not cashflow_df.empty else []
                }
                
                data[symbol] = fundamental_data
                
            except Exception as e:
                data[symbol] = {"error": str(e)}
        
        return {
            "data": data,
            "source": "tushare",
            "timestamp": datetime.now(),
            "period": period,
            "metrics": metrics
        }
    
    async def get_real_time_data(
        self,
        symbols: List[str],
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取实时数据
        
        Args:
            symbols: 股票代码列表
            fields: 数据字段列表
            
        Returns:
            实时数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        data = {}
        for symbol in symbols:
            try:
                ts_code = self._convert_symbol(symbol)
                
                # 获取实时行情（使用最新交易日数据模拟）
                df = self._api.daily(
                    ts_code=ts_code,
                    start_date=(datetime.now() - timedelta(days=5)).strftime("%Y%m%d"),
                    end_date=datetime.now().strftime("%Y%m%d")
                )
                
                if not df.empty:
                    latest = df.iloc[-1].to_dict()
                    data[symbol] = {
                        "last_price": latest.get("close"),
                        "volume": latest.get("vol"),
                        "timestamp": datetime.now()
                    }
                else:
                    data[symbol] = {"error": "No data available"}
                    
            except Exception as e:
                data[symbol] = {"error": str(e)}
        
        return {
            "data": data,
            "source": "tushare",
            "timestamp": datetime.now(),
            "fields": fields
        }
    
    def _convert_symbol(self, symbol: str) -> str:
        """
        转换股票代码格式
        
        Args:
            symbol: 原始股票代码
            
        Returns:
            Tushare格式的股票代码
        """
        # 简单的代码转换逻辑
        if "." in symbol:
            return symbol
        
        if symbol.startswith("0") or symbol.startswith("3"):
            return f"{symbol}.SZ"
        elif symbol.startswith("6"):
            return f"{symbol}.SH"
        else:
            return symbol


class WindAdapter(DataAdapter):
    """
    Wind数据适配器
    
    提供Wind数据源的访问接口。
    """
    
    def __init__(self, username: str, password: str):
        """
        初始化Wind适配器
        
        Args:
            username: Wind用户名
            password: Wind密码
        """
        super().__init__("wind")
        self.username = username
        self.password = password
        self._w = None
    
    async def initialize(self) -> None:
        """初始化Wind连接"""
        try:
            from WindPy import w
            self._w = w
            result = self._w.start()
            if result.ErrorCode != 0:
                raise ConnectionError(f"Wind connection failed: {result.Data}")
            self._initialized = True
            self._connection = self._w
        except ImportError:
            raise ImportError("WindPy package not installed")
        except Exception as e:
            raise ConnectionError(f"Failed to initialize Wind: {e}")
    
    async def get_market_data(
        self,
        symbols: List[str],
        start_date: datetime,
        end_date: datetime,
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取市场数据
        
        Args:
            symbols: 股票代码列表
            start_date: 开始日期
            end_date: 结束日期
            fields: 数据字段列表
            
        Returns:
            市场数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        # Wind字段映射
        wind_fields = ",".join(fields)
        
        try:
            result = self._w.wsd(
                codes=",".join(symbols),
                fields=wind_fields,
                beginTime=start_date.strftime("%Y-%m-%d"),
                endTime=end_date.strftime("%Y-%m-%d")
            )
            
            if result.ErrorCode != 0:
                raise Exception(f"Wind API error: {result.Data}")
            
            # 处理返回数据
            data = {}
            for i, symbol in enumerate(symbols):
                symbol_data = []
                for j, date in enumerate(result.Times):
                    record = {"date": date}
                    for k, field in enumerate(fields):
                        if isinstance(result.Data[k], list):
                            record[field] = result.Data[k][j * len(symbols) + i]
                        else:
                            record[field] = result.Data[k]
                    symbol_data.append(record)
                data[symbol] = symbol_data
            
            return {
                "data": data,
                "source": "wind",
                "timestamp": datetime.now(),
                "fields": fields
            }
            
        except Exception as e:
            return {
                "data": {symbol: {"error": str(e)} for symbol in symbols},
                "source": "wind",
                "timestamp": datetime.now(),
                "error": str(e)
            }
    
    async def get_fundamental_data(
        self,
        symbols: List[str],
        metrics: List[str],
        period: str
    ) -> Dict[str, Any]:
        """
        获取基本面数据
        
        Args:
            symbols: 股票代码列表
            metrics: 财务指标列表
            period: 报告期间
            
        Returns:
            基本面数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        # Wind财务数据字段映射
        wind_metrics = ",".join(metrics)
        
        try:
            # 获取最近几个报告期的数据
            result = self._w.wss(
                codes=",".join(symbols),
                fields=wind_metrics,
                options=f"rptType=1;Period={period};N=4"  # 最近4期数据
            )
            
            if result.ErrorCode != 0:
                raise Exception(f"Wind API error: {result.Data}")
            
            # 处理返回数据
            data = {}
            for i, symbol in enumerate(symbols):
                symbol_data = {}
                for j, metric in enumerate(metrics):
                    if isinstance(result.Data[j], list):
                        symbol_data[metric] = result.Data[j][i]
                    else:
                        symbol_data[metric] = result.Data[j]
                data[symbol] = symbol_data
            
            return {
                "data": data,
                "source": "wind",
                "timestamp": datetime.now(),
                "period": period,
                "metrics": metrics
            }
            
        except Exception as e:
            return {
                "data": {symbol: {"error": str(e)} for symbol in symbols},
                "source": "wind",
                "timestamp": datetime.now(),
                "error": str(e)
            }
    
    async def get_real_time_data(
        self,
        symbols: List[str],
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取实时数据
        
        Args:
            symbols: 股票代码列表
            fields: 数据字段列表
            
        Returns:
            实时数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        try:
            result = self._w.wsq(
                codes=",".join(symbols),
                fields=",".join(fields)
            )
            
            if result.ErrorCode != 0:
                raise Exception(f"Wind API error: {result.Data}")
            
            # 处理返回数据
            data = {}
            for i, symbol in enumerate(symbols):
                symbol_data = {"timestamp": datetime.now()}
                for j, field in enumerate(fields):
                    if isinstance(result.Data[j], list):
                        symbol_data[field] = result.Data[j][i]
                    else:
                        symbol_data[field] = result.Data[j]
                data[symbol] = symbol_data
            
            return {
                "data": data,
                "source": "wind",
                "timestamp": datetime.now(),
                "fields": fields
            }
            
        except Exception as e:
            return {
                "data": {symbol: {"error": str(e)} for symbol in symbols},
                "source": "wind",
                "timestamp": datetime.now(),
                "error": str(e)
            }


class DatabaseAdapter(DataAdapter):
    """
    数据库适配器
    
    提供数据库存储和查询接口。
    """
    
    def __init__(self):
        """初始化数据库适配器"""
        super().__init__("database")
        self._engine = None
    
    async def initialize(self) -> None:
        """初始化数据库连接"""
        try:
            from ..config.database import create_async_engine
            self._engine = create_async_engine()
            self._initialized = True
            self._connection = self._engine
        except Exception as e:
            raise ConnectionError(f"Failed to initialize database: {e}")
    
    async def get_market_data(
        self,
        symbols: List[str],
        start_date: datetime,
        end_date: datetime,
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        从数据库获取市场数据
        
        Args:
            symbols: 股票代码列表
            start_date: 开始日期
            end_date: 结束日期
            fields: 数据字段列表
            
        Returns:
            市场数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        # 这里应该实现具体的数据库查询逻辑
        # 暂时返回空数据作为框架
        return {
            "data": {symbol: [] for symbol in symbols},
            "source": "database",
            "timestamp": datetime.now(),
            "fields": fields
        }
    
    async def get_fundamental_data(
        self,
        symbols: List[str],
        metrics: List[str],
        period: str
    ) -> Dict[str, Any]:
        """
        从数据库获取基本面数据
        
        Args:
            symbols: 股票代码列表
            metrics: 财务指标列表
            period: 报告期间
            
        Returns:
            基本面数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        # 这里应该实现具体的数据库查询逻辑
        # 暂时返回空数据作为框架
        return {
            "data": {symbol: {} for symbol in symbols},
            "source": "database",
            "timestamp": datetime.now(),
            "period": period,
            "metrics": metrics
        }
    
    async def store_data(
        self,
        data: Dict[str, Any],
        data_type: str,
        metadata: Optional[Dict[str, Any]] = None
    ) -> bool:
        """
        存储数据到数据库
        
        Args:
            data: 要存储的数据
            data_type: 数据类型
            metadata: 元数据
            
        Returns:
            存储是否成功
        """
        if not self._initialized:
            await self.initialize()
        
        try:
            # 这里应该实现具体的数据存储逻辑
            # 暂时返回True作为框架
            return True
        except Exception as e:
            return False


class BloombergAdapter(DataAdapter):
    """
    Bloomberg数据适配器
    
    提供Bloomberg数据源的访问接口。
    """
    
    def __init__(self, host: str = "localhost", port: int = 8194):
        """
        初始化Bloomberg适配器
        
        Args:
            host: Bloomberg API主机
            port: Bloomberg API端口
        """
        super().__init__("bloomberg")
        self.host = host
        self.port = port
        self._session = None
    
    async def initialize(self) -> None:
        """初始化Bloomberg连接"""
        try:
            import blpapi
            # 这里应该实现Bloomberg API连接逻辑
            # 暂时标记为已初始化
            self._initialized = True
        except ImportError:
            raise ImportError("blpapi package not installed")
        except Exception as e:
            raise ConnectionError(f"Failed to initialize Bloomberg: {e}")
    
    async def get_market_data(
        self,
        symbols: List[str],
        start_date: datetime,
        end_date: datetime,
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取市场数据
        
        Args:
            symbols: 股票代码列表
            start_date: 开始日期
            end_date: 结束日期
            fields: 数据字段列表
            
        Returns:
            市场数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        # 这里应该实现Bloomberg API调用逻辑
        # 暂时返回空数据作为框架
        return {
            "data": {symbol: [] for symbol in symbols},
            "source": "bloomberg",
            "timestamp": datetime.now(),
            "fields": fields
        }
    
    async def get_fundamental_data(
        self,
        symbols: List[str],
        metrics: List[str],
        period: str
    ) -> Dict[str, Any]:
        """
        获取基本面数据
        
        Args:
            symbols: 股票代码列表
            metrics: 财务指标列表
            period: 报告期间
            
        Returns:
            基本面数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        # 这里应该实现Bloomberg API调用逻辑
        # 暂时返回空数据作为框架
        return {
            "data": {symbol: {} for symbol in symbols},
            "source": "bloomberg",
            "timestamp": datetime.now(),
            "period": period,
            "metrics": metrics
        }


class AKShareAdapter(DataAdapter):
    """
    AKShare数据适配器
    
    提供AKShare数据源的访问接口，作为Tushare的补充数据源。
    """
    
    def __init__(self):
        """初始化AKShare适配器"""
        super().__init__("akshare")
        self._ak = None
    
    async def initialize(self) -> None:
        """初始化AKShare连接"""
        try:
            import akshare as ak
            self._ak = ak
            self._initialized = True
            self._connection = self._ak
        except ImportError:
            raise ImportError("akshare package not installed")
        except Exception as e:
            raise ConnectionError(f"Failed to initialize AKShare: {e}")
    
    async def get_market_data(
        self,
        symbols: List[str],
        start_date: datetime,
        end_date: datetime,
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取市场数据
        
        Args:
            symbols: 股票代码列表
            start_date: 开始日期
            end_date: 结束日期
            fields: 数据字段列表
            
        Returns:
            市场数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        data = {}
        for symbol in symbols:
            try:
                # 转换股票代码格式
                ak_symbol = self._convert_symbol(symbol)
                
                # 获取股票历史数据
                df = self._ak.stock_zh_a_hist(
                    symbol=ak_symbol,
                    period="daily",
                    start_date=start_date.strftime("%Y%m%d"),
                    end_date=end_date.strftime("%Y%m%d"),
                    adjust=""
                )
                
                if not df.empty:
                    # 重命名列以匹配标准格式
                    column_mapping = {
                        "日期": "date",
                        "开盘": "open",
                        "收盘": "close",
                        "最高": "high",
                        "最低": "low",
                        "成交量": "volume",
                        "成交额": "amount"
                    }
                    
                    df = df.rename(columns=column_mapping)
                    df['date'] = pd.to_datetime(df['date'])
                    df = df.sort_values('date')
                    
                    # 只返回请求的字段
                    available_fields = [f for f in fields if f in df.columns]
                    if available_fields:
                        df = df[['date'] + available_fields]
                    
                    data[symbol] = df.to_dict('records')
                else:
                    data[symbol] = []
                    
            except Exception as e:
                data[symbol] = {"error": str(e)}
        
        return {
            "data": data,
            "source": "akshare",
            "timestamp": datetime.now(),
            "fields": fields
        }
    
    async def get_fundamental_data(
        self,
        symbols: List[str],
        metrics: List[str],
        period: str
    ) -> Dict[str, Any]:
        """
        获取基本面数据
        
        Args:
            symbols: 股票代码列表
            metrics: 财务指标列表
            period: 报告期间
            
        Returns:
            基本面数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        data = {}
        for symbol in symbols:
            try:
                ak_symbol = self._convert_symbol(symbol)
                
                # 获取财务数据
                fundamental_data = {}
                
                # 获取利润表数据
                try:
                    income_df = self._ak.stock_financial_analysis_indicator(symbol=ak_symbol)
                    if not income_df.empty:
                        fundamental_data["income"] = income_df.to_dict('records')
                except Exception:
                    fundamental_data["income"] = []
                
                # 获取资产负债表数据
                try:
                    balance_df = self._ak.stock_balance_sheet_by_report_em(symbol=ak_symbol)
                    if not balance_df.empty:
                        fundamental_data["balance"] = balance_df.to_dict('records')
                except Exception:
                    fundamental_data["balance"] = []
                
                # 获取现金流量表数据
                try:
                    cashflow_df = self._ak.stock_cash_flow_sheet_by_report_em(symbol=ak_symbol)
                    if not cashflow_df.empty:
                        fundamental_data["cashflow"] = cashflow_df.to_dict('records')
                except Exception:
                    fundamental_data["cashflow"] = []
                
                data[symbol] = fundamental_data
                
            except Exception as e:
                data[symbol] = {"error": str(e)}
        
        return {
            "data": data,
            "source": "akshare",
            "timestamp": datetime.now(),
            "period": period,
            "metrics": metrics
        }
    
    async def get_real_time_data(
        self,
        symbols: List[str],
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取实时数据
        
        Args:
            symbols: 股票代码列表
            fields: 数据字段列表
            
        Returns:
            实时数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        data = {}
        for symbol in symbols:
            try:
                ak_symbol = self._convert_symbol(symbol)
                
                # 获取实时行情数据
                df = self._ak.stock_zh_a_spot_em()
                
                # 查找对应股票的实时数据
                stock_data = df[df['代码'] == ak_symbol]
                
                if not stock_data.empty:
                    latest = stock_data.iloc[0]
                    data[symbol] = {
                        "last_price": latest.get("最新价", 0),
                        "volume": latest.get("成交量", 0),
                        "amount": latest.get("成交额", 0),
                        "change": latest.get("涨跌幅", 0),
                        "timestamp": datetime.now()
                    }
                else:
                    data[symbol] = {"error": "No real-time data available"}
                    
            except Exception as e:
                data[symbol] = {"error": str(e)}
        
        return {
            "data": data,
            "source": "akshare",
            "timestamp": datetime.now(),
            "fields": fields
        }
    
    async def get_alternative_data(
        self,
        data_type: str,
        parameters: Dict[str, Any]
    ) -> Dict[str, Any]:
        """
        获取另类数据
        
        Args:
            data_type: 数据类型
            parameters: 查询参数
            
        Returns:
            另类数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        try:
            if data_type == "news":
                # 获取新闻数据
                df = self._ak.stock_news_em()
                return {
                    "data": df.to_dict('records') if not df.empty else [],
                    "source": "akshare",
                    "timestamp": datetime.now(),
                    "data_type": data_type
                }
            
            elif data_type == "macro":
                # 获取宏观经济数据
                df = self._ak.macro_china_gdp()
                return {
                    "data": df.to_dict('records') if not df.empty else [],
                    "source": "akshare",
                    "timestamp": datetime.now(),
                    "data_type": data_type
                }
            
            elif data_type == "industry":
                # 获取行业数据
                df = self._ak.stock_board_industry_name_em()
                return {
                    "data": df.to_dict('records') if not df.empty else [],
                    "source": "akshare",
                    "timestamp": datetime.now(),
                    "data_type": data_type
                }
            
            else:
                return {
                    "data": [],
                    "source": "akshare",
                    "timestamp": datetime.now(),
                    "error": f"Unsupported data type: {data_type}"
                }
                
        except Exception as e:
            return {
                "data": [],
                "source": "akshare",
                "timestamp": datetime.now(),
                "error": str(e)
            }
    
    def _convert_symbol(self, symbol: str) -> str:
        """
        转换股票代码格式
        
        Args:
            symbol: 原始股票代码
            
        Returns:
            AKShare格式的股票代码
        """
        # 移除可能的后缀
        if "." in symbol:
            symbol = symbol.split(".")[0]
        
        # AKShare使用纯数字代码
        return symbol


class BrokerAdapter(DataAdapter):
    """
    券商接口适配器基类
    
    提供券商接口的统一访问框架。
    """
    
    def __init__(self, broker_name: str, config: Dict[str, Any]):
        """
        初始化券商适配器
        
        Args:
            broker_name: 券商名称
            config: 配置信息
        """
        super().__init__(f"broker_{broker_name}")
        self.broker_name = broker_name
        self.config = config
        self._client = None
    
    async def initialize(self) -> None:
        """初始化券商连接"""
        # 子类需要实现具体的初始化逻辑
        self._initialized = True
    
    async def get_market_data(
        self,
        symbols: List[str],
        start_date: datetime,
        end_date: datetime,
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取市场数据
        
        Args:
            symbols: 股票代码列表
            start_date: 开始日期
            end_date: 结束日期
            fields: 数据字段列表
            
        Returns:
            市场数据字典
        """
        # 基类提供默认实现，子类可以重写
        return {
            "data": {symbol: [] for symbol in symbols},
            "source": self.name,
            "timestamp": datetime.now(),
            "fields": fields
        }
    
    async def get_fundamental_data(
        self,
        symbols: List[str],
        metrics: List[str],
        period: str
    ) -> Dict[str, Any]:
        """
        获取基本面数据
        
        Args:
            symbols: 股票代码列表
            metrics: 财务指标列表
            period: 报告期间
            
        Returns:
            基本面数据字典
        """
        # 基类提供默认实现，子类可以重写
        return {
            "data": {symbol: {} for symbol in symbols},
            "source": self.name,
            "timestamp": datetime.now(),
            "period": period,
            "metrics": metrics
        }
    
    async def get_real_time_data(
        self,
        symbols: List[str],
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取实时数据
        
        Args:
            symbols: 股票代码列表
            fields: 数据字段列表
            
        Returns:
            实时数据字典
        """
        # 基类提供默认实现，子类可以重写
        return {
            "data": {symbol: {} for symbol in symbols},
            "source": self.name,
            "timestamp": datetime.now(),
            "fields": fields
        }
    
    async def get_account_info(self) -> Dict[str, Any]:
        """
        获取账户信息
        
        Returns:
            账户信息字典
        """
        # 子类需要实现具体逻辑
        raise NotImplementedError(f"Account info not implemented for {self.broker_name}")
    
    async def get_positions(self) -> Dict[str, Any]:
        """
        获取持仓信息
        
        Returns:
            持仓信息字典
        """
        # 子类需要实现具体逻辑
        raise NotImplementedError(f"Positions not implemented for {self.broker_name}")
    
    async def get_orders(self, status: Optional[str] = None) -> Dict[str, Any]:
        """
        获取订单信息
        
        Args:
            status: 订单状态过滤
            
        Returns:
            订单信息字典
        """
        # 子类需要实现具体逻辑
        raise NotImplementedError(f"Orders not implemented for {self.broker_name}")


class CustomDataAdapter(DataAdapter):
    """
    自定义数据源适配器
    
    提供自定义数据源的接入框架。
    """
    
    def __init__(self, name: str, data_source_config: Dict[str, Any]):
        """
        初始化自定义数据适配器
        
        Args:
            name: 适配器名称
            data_source_config: 数据源配置
        """
        super().__init__(name)
        self.config = data_source_config
        self._data_fetcher = None
    
    async def initialize(self) -> None:
        """初始化自定义数据源"""
        # 根据配置初始化数据获取器
        source_type = self.config.get("type", "api")
        
        if source_type == "api":
            self._data_fetcher = self._create_api_fetcher()
        elif source_type == "file":
            self._data_fetcher = self._create_file_fetcher()
        elif source_type == "database":
            self._data_fetcher = self._create_database_fetcher()
        else:
            raise ValueError(f"Unsupported data source type: {source_type}")
        
        self._initialized = True
    
    def _create_api_fetcher(self):
        """创建API数据获取器"""
        # 实现API数据获取逻辑
        pass
    
    def _create_file_fetcher(self):
        """创建文件数据获取器"""
        # 实现文件数据获取逻辑
        pass
    
    def _create_database_fetcher(self):
        """创建数据库数据获取器"""
        # 实现数据库数据获取逻辑
        pass
    
    async def get_market_data(
        self,
        symbols: List[str],
        start_date: datetime,
        end_date: datetime,
        fields: List[str]
    ) -> Dict[str, Any]:
        """
        获取市场数据
        
        Args:
            symbols: 股票代码列表
            start_date: 开始日期
            end_date: 结束日期
            fields: 数据字段列表
            
        Returns:
            市场数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        # 使用配置的数据获取器获取数据
        # 这里提供基础框架，具体实现根据数据源类型而定
        return {
            "data": {symbol: [] for symbol in symbols},
            "source": self.name,
            "timestamp": datetime.now(),
            "fields": fields
        }
    
    async def get_fundamental_data(
        self,
        symbols: List[str],
        metrics: List[str],
        period: str
    ) -> Dict[str, Any]:
        """
        获取基本面数据
        
        Args:
            symbols: 股票代码列表
            metrics: 财务指标列表
            period: 报告期间
            
        Returns:
            基本面数据字典
        """
        if not self._initialized:
            await self.initialize()
        
        return {
            "data": {symbol: {} for symbol in symbols},
            "source": self.name,
            "timestamp": datetime.now(),
            "period": period,
            "metrics": metrics
        }